{"id":"W976371631","doi":"","title":"Evaluation of Signal Retiming Measures Using Bluetooth Travel Time Data","year":2015,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Bluetooth and Wireless Communication Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Retiming; Bluetooth; SIGNAL (programming language); Computer science; Real-time computing; Telecommunications; Algorithm; Programming language; Wireless","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00247879,0.0005744896,0.0002487724,0.002215161,0.0004048296,0.0007994229,0.0007804374,0.0003647735,0.0009045079],"category_scores_gemma":[0.01011755,0.0001683828,0.0002187833,0.00167777,0.0003079341,0.0008465686,0.0004245334,0.0003659977,0.0003023271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007095433,"about_ca_system_score_gemma":0.0006967849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008821347,"about_ca_topic_score_gemma":0.01697882,"domain_scores_codex":[0.9977877,0.0006356132,0.0001795043,0.0002458942,0.0009999343,0.0001512883],"domain_scores_gemma":[0.9910353,0.002259926,0.001583015,0.000753718,0.004087287,0.0002808716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001893867,0.001716847,0.5975392,0.0006413567,0.0003110759,0.0003937644,0.00269616,0.04851986,0.0417776,0.00228525,0.003269291,0.2989557],"study_design_scores_gemma":[0.0001388854,0.01024937,0.8256028,0.0001408487,0.0002289768,0.0003357107,0.005514253,0.1032795,0.04508751,0.0009293523,0.008324848,0.0001680031],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9708421,0.0001077979,0.02170431,0.00006529639,0.00004428269,0.0004422916,0.0008351234,0.0002379265,0.005720813],"genre_scores_gemma":[0.9821686,0.0001016201,0.01536772,0.00003209998,0.00001140953,0.0002733162,0.0007385949,0.00002308748,0.001283624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008821347,"threshold_uncertainty_score":0.01753998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1009895482006826,"score_gpt":0.2808734674601403,"score_spread":0.1798839192594577,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}